Given the remarkable advance in computational power over the past decade, why has molecular simulation not had a more significant impact on the drug discovery process? While there are certainly noteworthy successes, the impact of virtual screening is limited by approximate treatment of ligand-protein interactions along two orthogonal dimensions: (1) Incorporation of backbone flexibility of the receptor, and (2) The accuracy with which molecular interactions are computed at the atomic level. The first Aim seeks a solution to issue (1) by proposing a novel approach to virtual screening by targeting ensembles of receptor conformations, as sampled in native like environments during microsecond timescale simulation. In contrast to previous efforts, the present proposal suggests a computationally expedient solution to the problem of estimating the entropy of binding. The second Aim seeks a solution to problem (2) by developing a new class of intermolecular potential based on recent advances in the quantum mechanical treatment of weak nonbonded interactions. Previously published results indicate at least a factor of five improvement in accuracy over standard empirical approaches. By bringing these advances to the field of protein-ligand interactions, dramatic improvement in the accuracy of these calculations is expected. Both Aims will be pursued in the context of the A2A adenosine receptor, a member of the G-protein coupled receptor family and a target for several disorders of the central nervous system, including Parkinson's disease. Hits identified from small molecule libraries will be experimentally validated via a collaboration with a lab with extensive expertise in A2A biochemistry. We will also apply our methods to the optimization of a series of androgen receptor antagonists developed at UD, with the long term goal of treating prostate cancer. Overall, success in either Aim will have a profound and widespread, positive impact on the predictive validity of calculations of small molecule-protein interactions. This will in turn improve the value of hits identified in virtual screens, and help to realize the predictive promise of virtual screening.